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Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization

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Tsinghua science and Technology 2024年第3期29卷 806-817页

作者： Lei Zeng Qi Liu Shigen Shen Xiaodong Liu school of Computer science Nanjing University of Information Science and TechnologyNanjing 210044China school of Software Nanjing University of Information Science and TechnologyNanjing 210044China school of information Engineering Huzhou UniversityHuzhou 313000China school of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

Edge computing nodes undertake an increasing number of tasks with the rise of business ***,how to efficiently allocate large-scale and dynamic workloads to edge computing resources has become a critical *** study proposes an edge task scheduling approach based on an improved Double Deep Q Network(DQN),which is adopted to separate the calculations of target Q values and the selection of the action in two networks.A new reward function is designed,and a control unit is added to the experience replay unit of the *** management of experience data are also modified to fully utilize its value and improve learning *** learning agents usually learn from an ignorant state,which is *** such,this study proposes a novel particle swarm optimization algorithm with an improved fitness function,which can generate optimal solutions for task *** optimized solutions are provided for the agent to pre-train network parameters to obtain a better cognition *** proposed algorithm is compared with six other methods in simulation *** show that the proposed algorithm outperforms other benchmark methods regarding makespan.

关键词： edge computing task scheduling reinforcement learning makespan Double Deep Q Network(DQN)

Protein acetylation sites with complex-valued polynomial model

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Frontiers of Computer science 2024年第3期18卷 217-226页

作者： Wenzheng BAO Bin YANG school of information Engineering Xuzhou University of TechnologyXuzhou 221018China school of information science and Engineering Zaozhuang UniversityZaozhuang 277160China

Protein acetylation refers to a process of adding acetyl groups(CH3CO-)to lysine residues on protein *** one of the most commonly used protein post-translational modifications,lysine acetylation plays an important role in different *** our study,we developed a humanspecific method which uses a cascade classifier of complexvalued polynomial model(CVPM),combined with sequence and structural feature descriptors to solve the problem of imbalance between positive and negative *** gene expression programming and differential evolution are utilized to search the optimal CVPM *** also made a systematic and comprehensive analysis of the acetylation data and the prediction *** performances of our proposed method are 79.15%in Sp,78.17%in Sn,78.66%in ACC 78.76%in F1,and 0.5733 in MCC,which performs better than other state-of-the-art methods.

关键词： protein acetylation complex-valued polynomial model machine learning

PCA-Net: a heart segmentation model based on the meta-learning method

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Optoelectronics Letters 2024年第11期20卷 697-704页

作者： YANG Mengzhu ZHU Dong DONG Hao HU Shunbo WANG Yongfang school of information science and Engineering Linyi University

In order to effectively prevent and treat heart-based diseases, the study of precise segmentation of heart parts is particularly important. The heart is divided into four parts: the left and right ventricles and the left and right atria, and the left main trunk is more important, thus the left ventricular muscle(LV-MYO), which is located in the middle part of the heart, has become the object of many researches.

关键词： A

CToMP: a cycle-task-oriented memory protection scheme for unmanned systems

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science China(information sciences) 2024年第6期67卷 399-417页

作者： Chengyan MA Ning XI Di LU Yebo FENG Jianfeng MA school of Cyber Engineering Xidian University school of Computer science and Technology Xidian University Department of Computer and information science University of Oregon

Memory corruption attacks(MCAs) refer to malicious behaviors of system intruders that modify the contents of a memory location to disrupt the normal operation of computing systems, causing leakage of sensitive data or perturbations to ongoing processes. Unlike general-purpose systems, unmanned systems cannot deploy complete security protection schemes, due to their limitations in size, cost and *** in unmanned systems are particularly difficult to defend against. Furthermore, MCAs have diverse and unpredictable attack interfaces in unmanned systems, severely impacting digital and physical sectors. In this paper, we first generalize, model and taxonomize MCAs found in unmanned systems currently, laying the foundation for designing a portable and general defense approach. According to different attack mechanisms,we found that MCAs are mainly categorized into two types — return2libc and return2shellcode. To tackle return2libc attacks, we model the erratic operation of unmanned systems with cycles and then propose a cycle-task-oriented memory protection(CToMP) approach to protect control flows from tampering. To defend against return2shellcode attacks, we introduce a secure process stack with a randomized memory address by leveraging the memory pool to prevent Shellcode from being executed. Moreover, we discuss the mechanism by which CTo MP resists the return-oriented programming(ROP) attack, a novel variant of return2libc attacks. Finally, we implement CTo MP on CUAV V5+ with Ardupilot and Crazyflie. The evaluation and security analysis results demonstrate that the proposed approach CTo MP is resilient to various MCAs in unmanned systems with low footprints and system overhead.

关键词： unmanned system memory corruption attack memory protection system security randomized memory address

Distributed Stochastic Optimization with Compression for Non-Strongly Convex Objectives

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Computer Modeling in Engineering & sciences 2024年第4期139卷 459-481页

作者： Xuanjie Li Yuedong Xu school of information science and Technology Fudan UniversityShanghaiChina

We are investigating the distributed optimization problem,where a network of nodes works together to minimize a global objective that is a finite sum of their stored local *** nodes exchange optimization parameters through the wireless network,large-scale training models can create communication bottlenecks,resulting in slower training *** address this issue,CHOCO-SGD was proposed,which allows compressing information with arbitrary precision without reducing the convergence rate for strongly convex objective ***,most convex functions are not strongly convex(such as logistic regression or Lasso),which raises the question of whether this algorithm can be applied to non-strongly convex *** this paper,we provide the first theoretical analysis of the convergence rate of CHOCO-SGD on non-strongly convex *** derive a sufficient condition,which limits the fidelity of compression,to guarantee ***,our analysis demonstrates that within the fidelity threshold,this algorithm can significantly reduce transmission burden while maintaining the same convergence rate order as its no-compression *** experiments further validate the theoretical findings by demonstrating that CHOCO-SGD improves communication efficiency and keeps the same convergence rate order *** experiments also show that the algorithm fails to converge with low compression fidelity and in time-varying ***,our study offers valuable insights into the potential applicability of CHOCO-SGD for non-strongly convex ***,we provide practical guidelines for researchers seeking to utilize this algorithm in real-world scenarios.

关键词： Distributed stochastic optimization arbitrary compression fidelity non-strongly convex objective function

A Review of NILM Applications with Machine Learning Approaches

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Computers, Materials & Continua 2024年第5期79卷 2971-2989页

作者： Maheesha Dhashantha Silva Qi Liu school of Electronic and information Engineering Nanjing University of Information Science and TechnologyNanjing210044China

In recent years,Non-Intrusive LoadMonitoring (NILM) has become an emerging approach that provides affordableenergy management solutions using aggregated load obtained from a single smart meter in the power ***, by integrating Machine Learning (ML), NILM can efficiently use electrical energy and offer less ofa burden for the energy monitoring process. However, conducted research works have limitations for real-timeimplementation due to the practical issues. This paper aims to identify the contribution of ML approaches todeveloping a reliable Energy Management (EM) solution with NILM. Firstly, phases of the NILM are discussed,along with the research works that have been conducted in the domain. Secondly, the contribution of machinelearning approaches in three aspects is discussed: Supervised learning, unsupervised learning, and *** highlights the limitations in the applicability of ML approaches in the field. Then, the challenges in the realtimeimplementation are concerned with six use cases: Difficulty in recognizing multiple loads at a given time,cost of running the NILM system, lack of universal framework for appliance detection, anomaly detection andnew appliance identification, and complexity of the electricity loads and real-time demand side ***, options for selecting an approach for an efficientNILMframework are suggested. Finally, suggestionsare provided for future research directions.

关键词： Non-intrusive load monitoring transfer learning machine learning feature extraction

Realization of Quantum Secure Direct Communication with Continuous Variable

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Research 2024年第2期6卷 159-170页

作者： Zhengwen Cao Yuan Lu Geng Chai Hao Yu Kexin Liang Lei Wang school of information science and Technology Northwest UniversityXi'an710127China

With the progress of theoretical and applied technologies,the communication system based on the classical encryption is seriously threatened by quantum computing and distributed computing.A communication method that directly loads confidential information on the quantum state,quantum secure direct communication(QSDC),came into being for resisting security ***,we report the first continuous-variable QSDC(CV-QSDC)experimental demonstration for verifying the feasibility and effectiveness of the CV-QSDC protocol based on Gaussian mapping and propose a parameter estimation for signal classification under the actual *** our experiment,we provided 4×10^(2) blocks,where each block contains 105 data for direct information *** the transmission distance of 5 km in our experiment,the excess noise is 0.0035 SNU,where SNU represents the unit of shot-noise *** 4.08×10^(5) bit per second experimental results firmly demonstrated the feasibility of CV-QSDC under the fiber *** proposed grading judgment method based on parameter estimation provides a practical and available message processing scheme for CV-QSDC in a practical fiber channel and lays the groundwork for the grading reconciliation.

关键词： quantum estimation verify

Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

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Chinese Physics B 2024年第4期33卷 729-734页

作者：鲁婕妤谢小华卢亚平吴亚联李春来马铭磷 school of Automation and Electronic information Xiangtan UniversityXiangtan 411105China school of Computer science school of Cyberspace science Xiangtan UniversityXiangtan 411105China

The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each *** memory characteristic of memristors makes them suitable for simulating neuronal synapses with *** this paper,a memristor is used to simulate a synapse,a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is *** explore the influence of system parameters on the dynamical behaviors of the discrete small-world network,and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameterαis *** results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network,and the higher the reconnection probability and number of the nearest neurons,the more significant the synchronization state of the *** addition,by increasing the coupling strength of memristor synapses,synchronization performance is *** results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

关键词： small-world networks Rulkov neurons memristor synchronization

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Joint modulation format identification and OSNR monitoring based on Stokes vector distribution features for digital coherent optical receivers

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Chinese Optics Letters 2024年第5期22卷 22-28页

作者：蒲正宇蒋林闫连山易安林何海军潘炜罗斌 Center for information Photonics&Communications School of Information Science and TechnologySouthwest Jiaotong UniversityChengdu 611756China

For joint modulation format identification(MFI)and optical signal-to-noise ratio(OSNR)monitoring,a simple and intelligent optical communication performance monitoring method is proposed,and the feasibility is demonstrated by digital coherent optical communication *** experiment results show that for all modulation formats,including 28 GBaud polarization division multiplexing(PDM)QPSK/8-QAM/16-QAM/64-QAM,100%MFI accuracies are achieved even at OSNR values lower than the corresponding theoretical 20%forward error correction limit,as well as the high accuracies for OSNR ***,the proposed scheme has a reasonable monitoring level when chromatic dispersion and fiber nonlinear effects are varied.

关键词： coherent communication optical performance monitoring deep neural network

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